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"Murray, D."
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Unsaturated soil mechanics in engineering practice
\"Here is the definitive guide to unsaturated soil by the world's expert in the area of unsaturated soil mechanics. This volume features the latest information and replaces the leading text in the field, also written by this author team. The text offers state-of-the-art information to deal with the practical engineering problems resulting from unsaturated soil. Greater emphasis has been placed on the using the soil-water characteristic curve in solving practical engineering problems, as well as the quantification of thermal and moisture boundary conditions based on weather data\"--
eBook
The development of the alternative Black curriculum, 1890-1940 : countering the master narrative
This book examines black intellectual thought during from 1890-1940, and its relationship to the development of the alternative black curriculum in social studies. Inquiry into the alternative black curriculum is a multi-disciplinary project; it requires an intersectional approach that draws on social studies research, educational history and black history. The alternative black curriculum demonstrates how black educators critiqued more prominent education reform movements in the United States. Murray's comprehensive account shows how female authors, intellectuals and teachers created complex narratives that challenged dominant discourses. Exploring the gendered construction of the alternative black curriculum, Murray considers the impact of Carter G. Woodson and W.E.B. DuBois in creating the alternative black curriculum in social studies, and its subsequent relationship to the work of black women in the social studies field.
Book
Ice Concentration Scaling Laws for Freshwater Lakes in Numerical Weather and Climate Prediction
If lake ice is assumed to deform and fail as a linear viscoelastic material under the action of wind stress, then a simple ice concentration scaling law can be constructed suitable for one‐dimensional lake models embedded within environmental prediction systems. Most 1‐D lake models assume no ice mechanics at all, while others adapt the viscous‐plastic rheology common in ice‐ocean models for the purpose of estimating ice fraction. Elastic buckling is generally disregarded as a significant failure mechanism in ice under low stress conditions at geophysical scales. However, by adding viscosity to the constitutive equation, the conditions for viscoelastic buckling seem quite plausible over a wide range of lake size and ice thickness. An ice concentration scaling law based on this process is evaluated here in multiannual simulations over North America and found to produce superior ice phenology statistics compared with simulations based on plastic failure or no ice mechanics. Plain Language Summary Most mid‐ and high‐latitude lakes experience periods of partial ice cover (i.e., ice concentration < 100%) during early winter. While very small lakes might freeze solid in a single night under calm conditions, larger lakes may take days or weeks to completely freeze because wind stress continually breaks the ice cover resulting in patches of open water. The extent of wintertime open water is very important for both lake ecology and for regional weather conditions (e.g., lake‐effect snowstorms). Many weather and climate models employ one‐dimensional lake models that do not represent fractional ice cover at all, or parameterize it based on mechanical ideas from sea ice models, resulting in poor timing and duration of simulated ice cover. Here we propose a new scheme based on different mechanics that improves these simulated features. Key Points Most one‐dimensional lake models neglect ice mechanics or assume plastic failure, and frequently perform poorly regarding ice phenology Assuming lake ice fails as a linear viscoelastic material at geophysical scales leads to a simple parameterization of ice concentration The new scheme outperforms plastic failure or the absence of mechanics with respect to ice—on and ice duration
Journal Article
Who is R.L. Stine?
\"Reader beware! The biography of R. L. Stine, author of the hugely popular Goosebumps series, is a scary-good time! R. L. Stine began writing stories at the age of nine, after finding a typewriter in his family's attic. (Was it a haunted typewriter? Who can be sure?) Often referred to as the 'Stephen King of children's literature,' R.L. has created some of the scariest books to have ever been passed around a campfire, leaving readers wide awake at night. With over 400 million copies of his horror fiction novels sold across the world, R.L. Stine is one of the best-selling authors in history\"-- Provided by publisher.
BOOK
Generative modeling of brain maps with spatial autocorrelation
Studies of large-scale brain organization have revealed interesting relationships between spatial gradients in brain maps across multiple modalities. Evaluating the significance of these findings requires establishing statistical expectations under a null hypothesis of interest. Through generative modeling of synthetic data that instantiate a specific null hypothesis, quantitative benchmarks can be derived for arbitrarily complex statistical measures. Here, we present a generative null model, provided as an open-access software platform, that generates surrogate maps with spatial autocorrelation (SA) matched to SA of a target brain map. SA is a prominent and ubiquitous property of brain maps that violates assumptions of independence in conventional statistical tests. Our method can simulate surrogate brain maps, constrained by empirical data, that preserve the SA of cortical, subcortical, parcellated, and dense brain maps. We characterize how SA impacts p-values in pairwise brain map comparisons. Furthermore, we demonstrate how SA-preserving surrogate maps can be used in gene set enrichment analyses to test hypotheses of interest related to brain map topography. Our findings demonstrate the utility of SA-preserving surrogate maps for hypothesis testing in complex statistical analyses, and underscore the need to disambiguate meaningful relationships from chance associations in studies of large-scale brain organization.
•Spatial autocorrelation can dramatically inflate p-values in brain map analyses.•Null model generates surrogate brain maps matched to target spatial autocorrelation.•Spatial autocorrelation drives spurious findings in gene set enrichment analyses.•Surrogate maps can correct statistical analyses including gene set enrichment.•Python-based package implements the generative model with neuroimaging functionality.
Journal Article
World War II. The Pacific
Written from a British perspective, this book discusses some of the key moments during the Pacific campaigns of World War II, along with personal anecdotes of soldiers and civilians.
Book
Multimodal gradients across mouse cortex
The primate cerebral cortex displays a hierarchy that extends from primary sensorimotor to association areas, supporting increasingly integrated function underpinned by a gradient of heterogeneity in the brain’s microcircuits. The extent to which these hierarchical gradients are unique to primate or may reflect a conserved mammalian principle of brain organization remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1-weighted:T2-weighted (T1w:T2w) magnetic resonance imaging map as a common spatial reference for comparison across species, we report interspecies agreement in a range of large-scale cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex, as well as notable interspecies differences. Our results support the view of systematic structural variation across cortical areas as a core organizational principle that may underlie hierarchical specialization in mammalian brains.
Journal Article
Australian peacekeeping : sixty years in the field
\"Peacekeeping has been a significant part of Australia's overseas military engagement since the end of the Second World War. Yet it is part of our history that has been largely neglected until the 1990s, and even since then interest has been slow to develop. In the last sixty years, between 30,000 and 40,000 Australian military personnel and police have served in more than 50 peacekeeping missions in at least 27 different conflicts. From the first Australian mission to Indonesia in 1947 to operations in East Timor, Bosnia and Rwanda among others, this book finally gives Australian peacekeeping its proper status. This work approaches Australian peacekeeping from four angles: its history, its agencies, some personal reflections, and its future. Contributors discuss the distinction between peacekeeping and war-fighting, the importance of peacekeeping in terms of public policy, the problems of multinational command, and the specialist contributions of the military, civilian police, mine-clearers, weapons inspectors and diplomats. The collection concludes with experts in the field including Tim Ford, a former Military Adviser to the UN Secretary-General, and distinguished academic Ramesh Thakur offering their perspectives on future directions for Australian peacekeeping.\"--Provided by publisher.
Book
Multitask representations in the human cortex transform along a sensory-to-motor hierarchy
Human cognition recruits distributed neural processes, yet the organizing computational and functional architectures remain unclear. Here, we characterized the geometry and topography of multitask representations across the human cortex using functional magnetic resonance imaging during 26 cognitive tasks in the same individuals. We measured the representational similarity across tasks within a region and the alignment of representations between regions. Representational alignment varied in a graded manner along the sensory–association–motor axis. Multitask dimensionality exhibited compression then expansion along this gradient. To investigate computational principles of multitask representations, we trained multilayer neural network models to transform empirical visual-to-motor representations. Compression-then-expansion organization in models emerged exclusively in a rich training regime, which is associated with learning optimized representations that are robust to noise. This regime produces hierarchically structured representations similar to empirical cortical patterns. Together, these results reveal computational principles that organize multitask representations across the human cortex to support multitask cognition.
What are the representations that enable diverse human cognition? The authors investigate cortical representations across 26 tasks and the conditions by which artificial neural network models reproduce these representations.
Journal Article